The Rise of EdTech Platforms in Higher Education: Mapping Themes from Emerging Critical Literature

Perspective Chapter: Educational Technology under Scrutiny in Higher Education – A Framework for Balancing Environmental, Economic and Social Aspects in a Blended Design

“…Digital data gain value through processes like extracting meaningful information, enclosing it, storing, aggregating, analysing and transforming it into intelligence. This encompasses various sources, ranging from scholarly discussions in virtual learning environments to user behaviour data, including click-throughs on platforms, as well as metadata detailing users' devices, location and internet protocol addresses [19,21].…”

“…The "use of deep neural networks within assetisation can by its very nature be not inspectable and thus inherently opaque. It involves complex, multi-stage decisions hard to scrutinise with human oversight" ( [21], p. 21). There are multiple options for creating a return on student platform data.…”

“…Despite these promising opportunities, HE seems reluctant to implement LA or AIED solutions [25]. A constraining factor for the adoption of LA or AIED seems to be the advanced digital competencies a teacher needs to improve their teaching methods with AI-based functionalities [21,25]. AI-based methods analyse the pattern of collected student platform data for developing the algorithms that can support the individual learner.…”

“…The learning content needs updating from time to time but online lectures can be watched multiple times. The reason this alliance is of interest to universities is that in countries worldwide the public sector, which includes education, is focused on efficiency, performance measurement, quality management, marketisation and accountability [5,21].…”